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Design of Disturbance Extended State Observer (D-ESO)-Based Constrained Full-State Model Predictive Controller for the Integrated Turbo-Shaft Engine/Rotor System

Author

Listed:
  • Nannan Gu

    (School of Energy and Power Engineering, Beihang University, Beijing 100191, China)

  • Xi Wang

    (School of Energy and Power Engineering, Beihang University, Beijing 100191, China
    Collaborative Innovation Center for Advanced Aeroengine, Beijing 100191, China)

  • Feiqiang Lin

    (Collaborative Innovation Center for Advanced Aeroengine, Beijing 100191, China)

Abstract

In the modern helicopter design and development process, constrained full-state control technology for turbo-shaft engine/rotor systems has always been a research hotspot in academia and industry. However, relevant references have pointed out that the traditional design method with an overly complex structure (Min-Max structure and schedule-based transient controller, i.e., M-M-STC) may not be able to meet the protection requirements of engine control systems under certain circumstances and can be too conservative under other conditions. In order to address the engine limit protection problem more efficiently, a constrained full-state model predictive controller (MPC) has been designed in this paper by incorporating a linear parameter varying (LPV) predictive model. Meanwhile, disturbance extended state observer (D-ESO) (which a sufficient convergence condition is deduced for) has also been proposed as the compensator of the LPV model to alleviate the MPC model mismatch problem. Finally, we run a group of comparison simulations with the traditional M-M-STC method to verify the effectiveness of this controller by taking compressor surge prevention problems as a case study, and the results indicate the validity of the proposed method.

Suggested Citation

  • Nannan Gu & Xi Wang & Feiqiang Lin, 2019. "Design of Disturbance Extended State Observer (D-ESO)-Based Constrained Full-State Model Predictive Controller for the Integrated Turbo-Shaft Engine/Rotor System," Energies, MDPI, vol. 12(23), pages 1-24, November.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4496-:d:290979
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    Citations

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    Cited by:

    1. Penghui Sun & Xi Wang & Shubo Yang & Bei Yang & Huairong Chen & Bin Wang, 2021. "Bumpless Transfer of Uncertain Switched System and Its Application to Turbofan Engines," Energies, MDPI, vol. 14(16), pages 1-21, August.
    2. Ziyu Gu & Shuwei Pang & Wenxiang Zhou & Yuchen Li & Qiuhong Li, 2022. "An Online Data-Driven LPV Modeling Method for Turbo-Shaft Engines," Energies, MDPI, vol. 15(4), pages 1-19, February.

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